%0 Journal Article %A Sara Lindström %A Stephanie Loomis %A Constance Turman %A Hongyan Huang %A Jinyan Huang %A Hugues Aschard %A Andrew T. Chan %A Hyon Choi %A Marilyn Cornelis %A Gary Curhan %A Immaculata De Vivo %A A. Heather Eliassen %A Charles Fuchs %A Michael Gaziano %A Susan E. Hankinson %A Frank Hu %A Majken Jensen %A Jae H. Kang %A Christopher Kabrhel %A Liming Liang %A Louis R. Pasquale %A Eric Rimm %A Meir J. Stampfer %A Rulla M. Tamimi %A Shelley S. Tworoger %A Janey L. Wiggs %A David J. Hunter %A Peter Kraft %T A comprehensive survey of genetic variation in 20,691 subjects from four large cohorts %D 2016 %R 10.1101/083030 %J bioRxiv %P 083030 %X The Nurses’ Health Study (NHS), Nurses’ Health Study II (NHSII), Health Professionals Follow Up Study (HPFS) and the Physicians Health Study (PHS) have collected detailed longitudinal data on multiple exposures and traits for approximately 310,000 study participants over the last 35 years. Over 160,000 study participants across the cohorts have donated a DNA sample and to date, 20,691 subjects have been genotyped as part of genome-wide association studies (GWAS) of twelve primary outcomes. However, these studies utilized six different GWAS arrays making it difficult to conduct analyses of secondary phenotypes or share controls across studies. To allow for secondary analyses of these data, we have created three new datasets merged by platform family and performed imputation using a common reference panel, the 1,000 Genomes Phase I release. Here, we describe the methodology behind the data merging and imputation and present imputation quality statistics and association results from two GWAS of secondary phenotypes (body mass index (BMI) and venous thromboembolism (VTE)).We observed the strongest BMI association for the FTO SNP rs55872725 (β=0.45, p=3.48×10−22), and using a significance level of p=0.05, we replicated 19 out of 32 known BMI SNPs. For VTE, we observed the strongest association for the rs2040445 SNP (OR=2.17, 95% CI: 1.79-2.63, p=2.70×10−15), located downstream of F5 and also observed significant associations for the known ABO and F11 regions. This pooled resource can be used to maximize power in GWAS of phenotypes collected across the cohorts and for studying gene-environment interactions as well as rare phenotypes and genotypes. %U https://www.biorxiv.org/content/biorxiv/early/2016/10/25/083030.full.pdf